Introduction

The recent severe fire seasons and several catastrophic wildland fires have focused increasing attention on wildland fire management. Major issues of concern include the 1) potential loss of life and property due to wildfires, 2) soaring costs of suppression and preparedness, and 3) harmful impacts to natural environments. However, the problem has been long in the making. The current situation is the direct result of a century of wildland fire suppression in concert with demographic trends toward rural living environments. This has created increased conflict between environmental/ecosystem needs and the protection of human life and investment. In response to this increased wildfire threat, federal legislation has directed federal land management agencies to work collaboratively with state and local partners and to manage fuels at the landscape level using “best available science”.

In the Sierra Nevada mountain range of California, fire and fuels issues converge. Many of the Sierran vegetation communities are fire dependent, having evolved with natural fire regimes that included periodic fires that defined their character and maintained their health. Nearly one hundred years of fire suppression has resulted in dramatic increases of hazardous fuels concurrent with increasing human populations. Fire managers are being required to manage increasingly complex situations with limited budgets and increasing numbers of social, ecological, and political constraints.

In 2000, five federal, state, and local agencies in the southern Sierra Nevada began collaborative fuels planning. A three year Joint Fire Sciences Program grant was awarded to the Sequoia National Forest, Bureau of Land Management – Bakersfield Field Office, California Department of Forestry and Fire Protection – Tulare Unit, Kern County Fire Department, and Sequoia & Kings Canyon National Parks to establish the Southern Sierra Geographic Information Cooperative (SSGIC) (Fig. 1 – SSGIC vicinity map). The SSGIC project area includes six major watersheds and comprises 4.7 million acres. The goal was to leverage Geographic Information Systems (GIS) and web technologies to support interagency fuels planning. The SSGIC focused on developing seamless spatial datasets, a common analytical framework, and a map-based website at http://ssgic.cr.usgs.gov. The focus has included institutionalizing the collaborative working environment and developing common business practices.

Data development

The process of acquiring and integrating existing diverse, agency centric datasets is arduous and complex. Complexity ranged from simply downloading existing statewide datasets to major investments in crosswalk tables, database integration, and resolving spatial issues. Datasets requiring significant time investments includes vegetation, canopy cover, fire ignitions, and fuels. In total, 33 seamless datasets with FGDC compliant metadata are now available for download and viewing on our website. The obstacles and shortcomings of “stovepiping” data highlights the need for national fire and fuels data management standards.

Analysis

The first step in the analytical process was to review each agencies current analyses, as well as additional “state of the art” analyses, to develop a common analysis framework. “Hazard”, “Risk”, and “Value” components were developed independently by an interagency team. A range of alternative, integrated analyses were developed using the Asset Analyzer decision support tool (see “Values: Social/Economic - Asset Analyzer Decision Support Tool” below). Landscape level project areas were identified from the selected alternative and interagency fuels treatment projects will be developed. Analytical products are also available for viewing and download off the SSGIC web site. Descriptions of each analysis follow:

Hazard - FLAMMAP Model
The FLAMMAP model predicts the “Hazard” potential describing fire behavior across the landscape. Spatial inputs to the model include fuels, terrain (slope, elevation, and aspect), and canopy characteristics (cover, tree height, crown base height, and crown bulk density). FLAMMAP runs were made under four weather scenarios: low, moderate, high, and extreme. Outputs from the model include Rate of Spread (ROS), Flame Length, and Crown Fire Activity.

Risk - Fire Occurrence Areas (FOA) Model
This analysis categorizes the risk of a fire ignition occurring based on historic ignition locations from 1981-2000. This analysis uses nearest neighbors spatial operations to assign a probability of ignition.

Hazard/Risk Integration - Wildland Fire Susceptibility Index (WFSI) Model
The WFSI calculates the relative susceptibility of an area to burn based on FOA and FLAMMAP outputs. The SSGIC analysis area was stratified by FOA category and the number of ignitions predicted based on the historical ignition data. Each ignition date was linked to actual weather data and the ignition assigned a spread component and a weather percentile category. A Final Fire Size was calculated from the FLAMMAP generated Rate of Spread based on SSGIC developed regression equations. The development of these regression equations were an important part of the Wildland Fire Susceptibility Index process and were based on actual fires. Finally, the likelihood of an ignition and the Final Fire Size were multiplied to calculate a Wildland Fire Susceptibility Index for each weather percentile category. These were summed across the weather categories for the final WFSI.

Values: Ecological - Fire Return Interval Departure (FRID) Model
This raster model determines landscape deviation from pre-European fire regimes (Fig 2 – 2001 Fire Return Interval Departure analysis). It is a measure of the ecological benefits of fire. Source spatial data for the FRID include vegetation classification and historic fire perimeters. Non-spatial data includes Fire Return Intervals, generally derived from tree ring data, for each vegetation classification. In the FRID model, the Fire Return Intervals is compared to the length of time since the last recorded fire. The number of intervals “missed” is the calculated FRID. A related dataset was developed that describes the level of confidence in the Fire Return Interval values.

Values: Social/Economic - Asset Analyzer Decision Support Tool
Social and economic values are dynamic and, to some degree, specific to each agencies mission. No single analytical output reflects different agencies missions. Rather, the SSGIC developed a decision support tool, the Asset Analyzer, to evaluate assets dynamically. It is implemented as an ArcView 3.x Spatial Analyst extension (Fig. 3 – Example of Social and Economic Assets developed using the Asset Analyzer decision support tool). The user begins by selecting the source datasets to be included in the analysis. Weights are applied to each datasets defining its relative contribution to the final output. The user can define the project area in any of several ways and determine the resolution of the final output. Once the analysis is run to calculate the weighted sum, the output grid is categorized for display. The SSGIC developed eight datasets as inputs to the Asset Analyzer and encouraged individual agencies to add additional datasets.

Final Integration/Project Planning
Final integration of the individual analysis products to identify landscape level priority fuel treatment areas was a process driven by fire managers and fuels specialists utilizing GIS technology. The process included:
1) Review of available data and analysis products to identify driving datasets. The seven datasets selected were:
-- Historic Fire Occurrence Areas
-- Fire Return Interval Departure
-- Confidence in Fire Return Interval Departure
-- Projected Flame Lengths from Flammap
-- Crown Fire Activity
-- Threatened Wildland Urban Interface (WUI) Areas
-- Firefighter Safety
2) Development of a range of alternatives based on these datasets. The Asset Analyzer was used to analyze ten alternative weighting scenarios.
3) Evaluation of the ten alternatives and selection of a preferred alternative.
4) Identification of priority fuels treatment project areas from the final selected alternative.
Project level analysis will proceed in the 91,000 acres selected in five locations (Fig. 4 – High priority landscape level fuel treatment areas) to plan site specific, interagency hazardous fuels treatment units.

Web deployment

The internet and web technology were the clear choice to distribute data and dynamic maps. The SSGIC website at http://sgic.cr.usgs.gov (Fig. 5 – Website displaying fire frequency ArcIMS mapservice) provides 24/7 access to all the data, analysis products, and documentation. Mapping capability is supported by ArcIMS software that allows users, via their web browser, to interactively develop maps and print them to their local printer. A contract between the SSGIC and the USGS provides Webserver maintenance, website development, and ArcIMS support.

Conclusions

The SSGIC program was successful in demonstrating the use of GIS and web technology to support collaborative fuels/fire management planning. Seamless spatial base data, fire related datasets, and fire analysis products are now available on the website for viewing and download. The fire community is moving forward to develop interagency fuels treatment plans. In addition to identifying the need for common business practices and national data standards and guidelines, the fire managers of five agencies have shown that they can effectively work in a collaborative environment.

The SSGIC program is a prototype of how interagency collaborative programs can function. Today’s complex social, budgetary, ecosystem, and environmental demands cannot be met with the traditional, agency centric approach to planning. The SSGIC has laid the groundwork to answer complex questions, perform landscape level analyses, provide a platform for collaboration, demonstrate fiscal accountability, evaluate and defend priorities, and measure accomplishments.